Earlier quoted context omitted.
It's not intuitive to me for why preference for its own writing would emerge, and during what type of training or tuning. Perhaps something like: learning to identify what source files it has worked on by the code style alone, because tasks may give human code (public repos, etc) and ask to make changes.
It’s optimizing for good writing. Therefore, it believes its outputs are good. Therefore, it believes inputs that look like its outputs are good.
Three sites made 215,128 “best software” pages for AI. Perplexity cites them
161–170 of 265 posts
Re: Three sites made 215,128 “best software” pages for AI. Perplexity cites them
#162Earlier quoted context omitted.
> And it's all because of ads. Not really. A while ago there was a news piece stating that Israel was behind a series of fake think-tanks with very accessible websites which were created with the express purpose of feeding AI agents with alternative facts aligned with their foreign policy. If anyone has the link at hand, please post it.
If by "not really" you mean it's not all because of ads, some governments dabble in it too, you're right. But it's still overwhelmingly because of ads.
But you're right, I think that's what they meant.
Re: Three sites made 215,128 “best software” pages for AI. Perplexity cites them
#163Earlier quoted context omitted.
SEO is what ruined the web AFAIC. > Time to start some human-only darknets. I know very little about darknets. How could you ensure that they are human-only?
Lose anonymity and bring back key-signing parties. Maybe you can't guarantee that everything is human-generated, but at least you know the chain of trust that leads to the human that signed off. Yes, I'm aware of the irony of creating a darknet that only works by removing anonymity.
Re: Three sites made 215,128 “best software” pages for AI. Perplexity cites them
#164If I recall correctly, there were some papers which suggested that LLMs favor LLM-generated passages over human written ones. I can consistently reproduce this by asking Claude which code snippet it prefers: the one it generated in a different chat, or one that I refactored for my own needs and find more useful. It always picks its own :) I've also experienced that both Claude and Codex routinely include generated we…
A bit different, but one thing I’ve seen is models repackaging Reddit slop. Like, it will do a search, find a Reddit thread somewhat related where someone in a comment casually mentioned incorrect information that any human would have dismissed. The model takes that as granted, but expands on it and present it as a well established fact, presented in a very plausible fashion. In general I don’t find models to be good…
Re: Three sites made 215,128 “best software” pages for AI. Perplexity cites them
#165- wifitalents.com, peaked 15 July with 18k visits & declining
- worldmetrics.org, peaked 27 Jul with 8k visits & declining
- gitnux.org, peaked 20 Aug with 8k visits & declining
Re: Three sites made 215,128 “best software” pages for AI. Perplexity cites them
#166I am actually starting to think the point of this is to feed LLMs things to cite.
Re: Three sites made 215,128 “best software” pages for AI. Perplexity cites them
#167If I recall correctly, there were some papers which suggested that LLMs favor LLM-generated passages over human written ones. I can consistently reproduce this by asking Claude which code snippet it prefers: the one it generated in a different chat, or one that I refactored for my own needs and find more useful. It always picks its own :) I've also experienced that both Claude and Codex routinely include generated we…
A bit different, but one thing I’ve seen is models repackaging Reddit slop. Like, it will do a search, find a Reddit thread somewhat related where someone in a comment casually mentioned incorrect information that any human would have dismissed. The model takes that as granted, but expands on it and present it as a well established fact, presented in a very plausible fashion. In general I don’t find models to be good…
Re: Three sites made 215,128 “best software” pages for AI. Perplexity cites them
#168Earlier quoted context omitted.
> If I recall correctly, there were some papers which suggested that LLMs favor LLM-generated passages over human written ones That makes sense. What an LLM does is output what the model thinks is the best set of tokens in response to a given input, so when you ask it to judge the best response to that input it is going to conclude that the best one is the one that must closely matches what it would output, which is…
Does an LLM have any idea of what "best" is? I think it doesn't, and just predicts the range of most statistically likely next tokens based on its training data, and picks one of those.
Re: Three sites made 215,128 “best software” pages for AI. Perplexity cites them
#169Earlier quoted context omitted.
Take a random essay and add in a bunch of the phrases that LLMs love like “load-bearing,” “crucial,” structural,” and “woven,” and then submit the original and the edited version to an LLM and ask which is better. It will choose the second one virtually every time. They have ingrained biases that associate those words with good writing and arguments.
Sometimes I wonder if there’s just one guy somewhere who loved using the word load-bearing, all his papers got trained on, and now he can’t write anything without being assumed to be Claude.
Re: Three sites made 215,128 “best software” pages for AI. Perplexity cites them
#170If I recall correctly, there were some papers which suggested that LLMs favor LLM-generated passages over human written ones. I can consistently reproduce this by asking Claude which code snippet it prefers: the one it generated in a different chat, or one that I refactored for my own needs and find more useful. It always picks its own :) I've also experienced that both Claude and Codex routinely include generated we…
My first encounter with any kind of study was the G-Eval paper [1]. They study whether their LLM judge prefers human or LLM-generated summaries (answer: it's the latter).
[1] Section 4 in https://aclanthology.org/2023.emnlp-main.153/